Title :
An efficient supervised clustering algorithm based on neural networks
Author_Institution :
Sch. of Inf. Eng., Inst. of Technol., Nanchang, China
Abstract :
Clustering is a fundamental technology in Artificial Intelligence. Radial basis function neural network (RBFN) is a kind of Artificial Neural Network with simple structure. In this paper, we introduce supervised clustering into RBFN and create a novel supervised fuzzy clustering network based on linear regression model which shows better results in regression task. We propose a novel local modeling technology based on fuzzy partition and supervised clustering which uses different algorithms according to each subset´s modeling difficulty respectively and thus overcomes its antecessors´ shortcomings.
Keywords :
artificial intelligence; fuzzy set theory; pattern clustering; radial basis function networks; regression analysis; artificial intelligence; fuzzy clustering network; linear regression; radial basis function neural network; supervised clustering algorithm; Clustering algorithms; Computational modeling; Clustering; Supervised; neural network;
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-6539-2
DOI :
10.1109/ICACTE.2010.5579840